• Keyvan Karkouti, Duminda N Wijeysundera, W Scott Beattie, Jeannie L Callum, Davy Cheng, Jean-Yves Dupuis, Blaine Kent, David Mazer, Fraser D Rubens, Corey Sawchuk, Terrence M Yau, and Reducing Bleeding in Cardiac Surgery (RBC) Research Group.
• University Health Network, Toronto General Hospital, Department of Anesthesia, Ontario, Canada. keyvan.karkouti@uhn.on.ca
• Transfusion. 2007 Nov 1;47(11):2081-8.

BackgroundIn cardiac surgery, excessive blood loss requiring large-volume red blood cell (RBC) transfusion is a common occurrence that is associated with significant morbidity and mortality. The objectives of this study were to measure the interinstitution variation and predictability of large-volume RBC transfusion.Study Design And MethodsData were retrospectively collected on 3500 consecutive cardiac surgical patients at seven Canadian hospitals during 2004. The crude and risk-adjusted institutional odds ratios (ORs) for large-volume (>or=5 U) RBC transfusion were calculated with logistic regression. The predictive accuracy of an existing prediction rule for large-volume RBC transfusion was calculated for each institution.ResultsLarge-volume RBC transfusion occurred in 538 (15%) patients. When compared to the reference hospital (median crude rate), the institutional unadjusted and adjusted ORs for large-volume RBC transfusion ranged from 0.29 to 1.26 and 0.14 to 1.15, respectively (p<0.0001 for interinstitution variation). The variation was lower, but still considerable, for excessive blood loss, defined as at least 5-U RBC transfusion or reexploration; the ORs ranged from 0.42 to 1.22 (p<0.0001). The prediction rule performed well at most sites; its pooled positive predictive value for excessive blood loss was 71 percent (range, 63%-89%), and its negative predictive value was 90 percent (range, 87%-93%).ConclusionsThere is marked interinstitution variation in large-volume RBC transfusion in cardiac surgery that is not explained by patient- or surgery-related factors. Despite this variation, patients at high or low risk for large-volume RBC transfusion can be accurately identified by a prediction rule composed of readily available clinical variables.

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